Optimizing the use of point of care testing devices for screening patients

Electronic health record data is unable to effectively characterize measurement error from pulse oximetry: a simulation study

Large data sets from electronic health records (EHR) have been used in journal articles to demonstrate race-based imprecision in pulse oximetry (SpO2) measurements. These articles do not appear to recognize the impact of the variability of the SpO2 values with respect to time ("deviation time"). This manuscript seeks to demonstrate that due to this variability, EHR data should not be used to quantify SpO2 error. Using the MIMIC-IV Waveform dataset, SpO2 values are sampled from 198 patients admitted to an intensive care unit and used as reference samples. The error derived from the EHR data is simulated using a set of deviation times. The laboratory oxygen saturation measurements are also simulated such that the performance of three simulated pulse oximeter devices will produce an average root mean squared (ARMS) error of 2%. An analysis is then undertaken to reproduce a medical device submission to a regulatory body by quantifying the mean error, the standard deviation of the error, and the ARMS error. Bland-Altman plots were also generated with their Limits of Agreements. Each analysis was repeated to evaluate whether the measurement errors were affected by increasing the deviation time. All error values increased linearly with respect to the logarithm of the time deviation. At 10 min, the ARMS error increased from a baseline of 2% to over 4%. EHR data cannot be reliably used to quantify SpO2 error. Caution should be used in interpreting prior manuscripts that rely on EHR data.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review

With the continuous discovery and research of predictive cancer-related biomarkers, liquid biopsy shows great potential in cancer diagnosis. Surface-enhanced Raman scattering (SERS) and microfluidic technology have received much attention among the various cancer biomarker detection methods. The former has ultrahigh detection sensitivity and can provide a unique fingerprint. In contrast, the latter has the characteristics of miniaturization and integration, which can realize accurate control of the detection samples and high-throughput detection through design. Both have the potential for point-of-care testing (POCT), and their combination (lab-on-a-chip SERS (LoC-SERS)) shows good compatibility. In this paper, the basic situation of circulating proteins, circulating tumor cells, exosomes, circulating tumor DNA (ctDNA), and microRNA (miRNA) in the diagnosis of various cancers is reviewed, and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail. At the same time, the challenges and future development of the platform are discussed at the end of the review. Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.